SlideShare uma empresa Scribd logo
1 de 19
Baixar para ler offline
Lustre 1.8.9 - 2.x Client Performance
Comparison and Tuning!
John Fragalla!
HPC Principal Architect!
Xyratex, A Seagate Company!
!
Lustre User Group Conference!
April 8-10, 2014!
• Benchmark Setup!
• IOR Parameters and Settings!
• Lustre Clients and Methodology!
• Single Thread Performance!
• Throughput Performance Results and Data!
• Summary!
Agenda!
!
• Storage Architecture!
– A Cluster 6000 SSU with GridRaid OSTs!
•  Rated Storage Performance ≥ 6 GB/s Read or Write with IOR!
– InfiniBand FDR Interconnect!
– Xyratex Lustre 2.1.0.x4-74!
• Client Hardware!
– 8 Clients, each configured with QDR IB, 48GB Memory and
12 Cores!
– Scientific Linux 6.5 with Stock OFED!
Benchmark Setup!
• Used mpirun to execute IOR with --byslot distribution!
• IOR Parameters that were constant:!
–  -F : File Per Process!
–  -B : Direct IO Operation!
–  -t 64m: 64m Transfer Size per Task!
–  -b: 1024g for Single Thread and 512g for multiple tasks!
–  -D: stonewall option, write for 4 minutes, and read for 2
minutes!
• Lustre Settings!
– Stripe Count of 1!
– Stripe Size of 1m!
IOR Parameters and Settings!
• Compared the following clients:!
– 1.8.9, 2.1.6, 2.4.3, and 2.5.1!
• Collected raw performance data using the following client
settings with and without checksums enabled!
– max_rpcs_in flight / max_dirty_mb!
•  32 / 128!
•  64 / 256!
•  128 / 512!
•  256 / 1024!
Lustre Clients!
Single Thread Write Performance!
0
200
400
600
800
1,000
1,200
32/128 64/256 128/512 256/1024
MB/s
Max PRCs / Max Dirty MB
Single Thread Client Write Performance - Checksums
Disabled
1.8.9 CS=0 Write (MB/s)
2.1.6 CS=0 Write (MB/s)
2.4.3 CS=0 Write (MB/s)
2.5.1 CS=0 Write (MB/s)
Single Thread Read Performance!
-
200.00
400.00
600.00
800.00
1,000.00
1,200.00
1,400.00
32/128 64/256 128/512 256/1024
MB/s
Max PRCs / Max Dirty MB
Single Thread Client Read Performance
Checksums Disabled
1.8.9 CS=0 Read (MB/s)
2.1.6 CS=0 Read (MB/s)
2.4.3 CS=0 Read (MB/s)
2.5.1 CS=0 Read (MB/s)
Impact on Single Thread Performance when
Checksums were Enabled!
 ! Checksums Impact - Single Thread!
 Version!  ! Reads! Writes!
1.8.9!
Performance Impact Difference (MB/s)! 217.80 ! 336.84 !
Percentage Impact Reduced! 19%! 35%!
2.1.6!
Performance Impact Difference (MB/s)! 37.70 ! 27.81 !
Percentage Impact Reduced! 3%! 6%!
2.4.3!
Performance Impact Difference (MB/s)! 45.51 ! 9.14 !
Percentage Impact Reduced! 6%! 1%!
2.5.1!
Performance Impact Difference (MB/s)! 44.91 ! 6.50 !
Percentage Impact Reduced! 6%! 1%!
1.8.9 Client Performance Results!
0
1,000
2,000
3,000
4,000
5,000
6,000
7,000
1 2 4 8 8 8
4 8 16 32 64 96
MB/s
Nodes and Tasks
1.8.9 Writes - Checksums Disabled
Write 32/128/0
Write 64/256/0
Write 128/512/0
Write 256/1024/0
-
1,000
2,000
3,000
4,000
5,000
6,000
7,000
8,000
1 2 4 8 8 8
4 8 16 32 64 96
MB/s
Nodes and Tasks
1.8.9 Reads - Checksums Disabled
Read 32/128/0
Read 64/256/0
Read 128/512/0
Read 256/1024/0
Key:
max_rpcs_in_flight / max_dirty_mb / checksums
2.1.6 Client Performance Results!
0
500
1,000
1,500
2,000
2,500
3,000
3,500
4,000
4,500
1 2 4 8 8 8
4 8 16 32 64 96
MB/s
Nodes and Tasks
2.1.6 Writes - Checksums Disabled
Write 32/128/0
Write 64/256/0
Write 128/512/0
Write 256/1024/0
0
1,000
2,000
3,000
4,000
5,000
6,000
1 2 4 8 8 8
4 8 16 32 64 96
MB/s
Nodes and Tasks
2.1.6 Reads - Checksums Disabled
Read 32/128/0
Read 64/256/0
Read 128/512/0
Read 256/1024/0
Key:
max_rpcs_in_flight / max_dirty_mb / checksums
2.4.3 Client Performance Results!
0
1,000
2,000
3,000
4,000
5,000
6,000
7,000
1 2 4 8 8 8
4 8 16 32 64 96
MB/s
Nodes and Tasks
2.4.3 Writes - Checksums Disabled
Write 32/128/0
Write 64/256/0
Write 128/512/0
Write 256/1024/0
0
1,000
2,000
3,000
4,000
5,000
6,000
7,000
8,000
1 2 4 8 8 8
4 8 16 32 64 96
MB/s
Nodes and Tasks
2.4.3 Reads - Checksums Disabled
Read 32/128/0
Read 64/256/0
Read 128/512/0
Read 256/1024/0
Key:
max_rpcs_in_flight / max_dirty_mb / checksums
2.5.1 Client Performance Results!
0
1,000
2,000
3,000
4,000
5,000
6,000
7,000
1 2 4 8 8 8
4 8 16 32 64 96
MB/s
Nodes and Tasks
2.5.1 Writes - Checksums Disabled
Write 32/128/0
Write 64/256/0
Write 128/512/0
Write 256/1024/0
0
1,000
2,000
3,000
4,000
5,000
6,000
7,000
8,000
1 2 4 8 8 8
4 8 16 32 64 96
MB/s
Nodes and Tasks
2.5.1 Reads - Checksums Disabled
Read 32/128/0
Read 64/256/0
Read 128/512/0
Read 256/1024/0
Key:
max_rpcs_in_flight / max_dirty_mb / checksums
Average Negative Impact on Performance
when Checksums Enabled!
Checksums Impact (max_rpcs_in_flight/max_dirty_mb)
Reads
32/128
Write
32/128
Read
64/256
Write
65/256
Read
128/512
Write
128/512
Read
256/1024
Write
256/1024
1.8.9
Average Impact
Difference (MB/s)
203.40 398.09 3.12 434.41 71.03 523.17 31.19 502.31
Average Impact
Percentage
2% 10% -1% 10% 0% 13% 0% 12%
2.1.6
Average Impact
Difference (MB/s)
541.64 269.93 446.17 196.06 445.79 189.33 453.34 180.07
Average Impact
Percentage
22% 12% 19% 9% 18% 8% 9% 8%
2.4.3
Average Impact
Difference (MB/s)
333.18 94.53 277.32 77.16 380.47 194.21 326.76 315.71
Average Impact
Percentage
7% 3% 5% 2% 7% 4% 5% 6%
2.5.1
Average Impact
Difference (MB/s)
486.11 161.09 245.24 154.50 366.05 256.85 346.78 423.12
Average Impact
Percentage
12% 5% 5% 4% 6% 6% 6% 9%
Average results using 4-96 Threads across 1-8 Clients
1.8.9, 2.4.3, 2.5.1 Overall Write Comparison!
0
1,000
2,000
3,000
4,000
5,000
6,000
7,000
1 2 4 8 8 8
4 8 16 32 64 96
MB/s
Nodes and Tasks
1.8.9, 2.4.3, 2.5.1 Writes Comparison - Checksums Disabled
1.8.9 Write 32/128/0
1.8.9 Write 64/256/0
1.8.9 Write 128/512/0
1.8.9 Write 256/1024/0
2.4.3 Write 32/128/0
2.4.3 Write 64/256/0
2.4.3 Write 128/512/0
2.4.3 Write 256/1024/0
2.5.1 Write 32/128/0
2.5.1 Write 64/256/0
2.5.1 Write 128/512/0
2.5.1 Write 256/1024/0
1.8.9, 2.4.3, 2.5.1 Overall Read Comparison!
0
1,000
2,000
3,000
4,000
5,000
6,000
7,000
8,000
1 2 4 8 8 8
4 8 16 32 64 96
MB/s
Nodes and Tasks
1.8.9, 2.4.3, 2.5.1 Reads Comparison - Checksums Disabled
1.8.9 Read 32/128/0
1.8.9 Read 64/256/0
1.8.9 Read 128/512/0
1.8.9 Read 256/1024/0
2.4.3 Read 32/128/0
2.4.3 Read 64/256/0
2.4.3 Read 128/512/0
2.4.3 Read 256/1024/0
2.5.1 Read 32/128/0
2.5.1 Read 64/256/0
2.5.1 Read 256/1024/0
2.5.1 Read 256/1024/0
Maximizing Performance for Each Client!
0
1,000
2,000
3,000
4,000
5,000
6,000
7,000
8,000
32 32 96 96 32 32 32 32
Read 32/128/0 Write 32/128/0 Read 128/512/0 Write 128/512/0 Read 256/1024/0Write 256/1024/0Read 256/1024/0Write 256/1024/0
1.8.9 2.1.6 2.4.3 2.5.1
MB/s
Client
Reads and Writes
RPCs/Dirty_MB/Checksums
Max Performance Comparison - Checksums Disabled
• In general, 1.8.9 Client performed the same regardless of
client settings!
• 2.4.3 and 2.5.1 followed the same performance curve!
– Clients settings need to be increased to achieve maximum
storage throughput!
– Both max_rpcs_in_flight and max_dirty_mb need to be
increased to at lest 256!
•  Anything less than 256 will result in less than optimal Storage
performance!
• The rule of thumb: max_dirty_mb = max_rpcs_in_flight * 4 

is not holding true with Client versions 2.4.3 and 2.5.1!
Interesting Results Analyzing Raw Data!
• 1.8.9 single thread performance results are the highest, but
2.4.3 and 2.5.1 improved over previous 2.x client versions!
• With the right client settings, 2.4.3 and 2.5.1 client versions
can maximize storage throughput, along with 1.8.9 clients!
• 2.1.6 Client underperformed, regardless of client tuning!
• Checksums impact varied with the number of threads, but,
on average, not a “big” performance impact!
– Biggest impact on performance with Checksums enabled
was on the Single Thread tests!
• 2.4.3 and 2.5.1 performance results were similar across all
threads and client tuning parameters!
Summary!
Thank You
John_Fragalla@xyratex.com

Mais conteúdo relacionado

Semelhante a Lustre client performance comparison and tuning (1.8.x to 2.x)

Journey to Stability: Petabyte Ceph Cluster in OpenStack Cloud
Journey to Stability: Petabyte Ceph Cluster in OpenStack CloudJourney to Stability: Petabyte Ceph Cluster in OpenStack Cloud
Journey to Stability: Petabyte Ceph Cluster in OpenStack CloudCeph Community
 
Journey to Stability: Petabyte Ceph Cluster in OpenStack Cloud
Journey to Stability: Petabyte Ceph Cluster in OpenStack CloudJourney to Stability: Petabyte Ceph Cluster in OpenStack Cloud
Journey to Stability: Petabyte Ceph Cluster in OpenStack CloudPatrick McGarry
 
Plextor mSATA M5M sales kits
Plextor mSATA M5M sales kitsPlextor mSATA M5M sales kits
Plextor mSATA M5M sales kitsMaarten Souren
 
Micron vPAK 2pp Final no Bleed_TD03
Micron vPAK 2pp Final no Bleed_TD03Micron vPAK 2pp Final no Bleed_TD03
Micron vPAK 2pp Final no Bleed_TD03Peyman Blumstengel
 
Ceph Day Berlin: Ceph on All Flash Storage - Breaking Performance Barriers
Ceph Day Berlin: Ceph on All Flash Storage - Breaking Performance BarriersCeph Day Berlin: Ceph on All Flash Storage - Breaking Performance Barriers
Ceph Day Berlin: Ceph on All Flash Storage - Breaking Performance BarriersCeph Community
 
Day 2 General Session Presentations RedisConf
Day 2 General Session Presentations RedisConfDay 2 General Session Presentations RedisConf
Day 2 General Session Presentations RedisConfRedis Labs
 
Hardware and Software Co-optimization to Make Sure Oracle Fusion Middleware R...
Hardware and Software Co-optimization to Make Sure Oracle Fusion Middleware R...Hardware and Software Co-optimization to Make Sure Oracle Fusion Middleware R...
Hardware and Software Co-optimization to Make Sure Oracle Fusion Middleware R...Intel IT Center
 
Cassandra TK 2014 - Large Nodes
Cassandra TK 2014 - Large NodesCassandra TK 2014 - Large Nodes
Cassandra TK 2014 - Large Nodesaaronmorton
 
Toshiba Storage Protfolio 2014
Toshiba Storage Protfolio 2014Toshiba Storage Protfolio 2014
Toshiba Storage Protfolio 2014Mustafa Kuğu
 
Alibaba cloud benchmarking report ecs rds limton xavier
Alibaba cloud benchmarking report ecs  rds limton xavierAlibaba cloud benchmarking report ecs  rds limton xavier
Alibaba cloud benchmarking report ecs rds limton xavierLimton Xavier
 
Ceph Day Taipei - Accelerate Ceph via SPDK
Ceph Day Taipei - Accelerate Ceph via SPDK Ceph Day Taipei - Accelerate Ceph via SPDK
Ceph Day Taipei - Accelerate Ceph via SPDK Ceph Community
 
5 Things You Need to Know About Enterprise Fl
 5 Things You Need to Know About Enterprise Fl 5 Things You Need to Know About Enterprise Fl
5 Things You Need to Know About Enterprise FlWestern Digital
 
Accelerating SSD Performance with HLNAND
Accelerating SSD Performance with HLNANDAccelerating SSD Performance with HLNAND
Accelerating SSD Performance with HLNANDrrschuetz
 
Big Lab Problems Solved with Spectrum Scale: Innovations for the Coral Program
Big Lab Problems Solved with Spectrum Scale: Innovations for the Coral ProgramBig Lab Problems Solved with Spectrum Scale: Innovations for the Coral Program
Big Lab Problems Solved with Spectrum Scale: Innovations for the Coral Programinside-BigData.com
 
VMware VSAN Technical Deep Dive - March 2014
VMware VSAN Technical Deep Dive - March 2014VMware VSAN Technical Deep Dive - March 2014
VMware VSAN Technical Deep Dive - March 2014David Davis
 
Understanding and Measuring I/O Performance
Understanding and Measuring I/O PerformanceUnderstanding and Measuring I/O Performance
Understanding and Measuring I/O PerformanceGlenn K. Lockwood
 
DevOps for ETL processing at scale with MongoDB, Solr, AWS and Chef
DevOps for ETL processing at scale with MongoDB, Solr, AWS and ChefDevOps for ETL processing at scale with MongoDB, Solr, AWS and Chef
DevOps for ETL processing at scale with MongoDB, Solr, AWS and ChefGaurav "GP" Pal
 
stackArmor presentation for DevOpsDC ver 4
stackArmor presentation for DevOpsDC ver 4stackArmor presentation for DevOpsDC ver 4
stackArmor presentation for DevOpsDC ver 4Gaurav "GP" Pal
 

Semelhante a Lustre client performance comparison and tuning (1.8.x to 2.x) (20)

Journey to Stability: Petabyte Ceph Cluster in OpenStack Cloud
Journey to Stability: Petabyte Ceph Cluster in OpenStack CloudJourney to Stability: Petabyte Ceph Cluster in OpenStack Cloud
Journey to Stability: Petabyte Ceph Cluster in OpenStack Cloud
 
Journey to Stability: Petabyte Ceph Cluster in OpenStack Cloud
Journey to Stability: Petabyte Ceph Cluster in OpenStack CloudJourney to Stability: Petabyte Ceph Cluster in OpenStack Cloud
Journey to Stability: Petabyte Ceph Cluster in OpenStack Cloud
 
Plextor mSATA M5M sales kits
Plextor mSATA M5M sales kitsPlextor mSATA M5M sales kits
Plextor mSATA M5M sales kits
 
Micron vPAK 2pp Final no Bleed_TD03
Micron vPAK 2pp Final no Bleed_TD03Micron vPAK 2pp Final no Bleed_TD03
Micron vPAK 2pp Final no Bleed_TD03
 
Ceph Day Berlin: Ceph on All Flash Storage - Breaking Performance Barriers
Ceph Day Berlin: Ceph on All Flash Storage - Breaking Performance BarriersCeph Day Berlin: Ceph on All Flash Storage - Breaking Performance Barriers
Ceph Day Berlin: Ceph on All Flash Storage - Breaking Performance Barriers
 
LUG 2014
LUG 2014LUG 2014
LUG 2014
 
Day 2 General Session Presentations RedisConf
Day 2 General Session Presentations RedisConfDay 2 General Session Presentations RedisConf
Day 2 General Session Presentations RedisConf
 
Hardware and Software Co-optimization to Make Sure Oracle Fusion Middleware R...
Hardware and Software Co-optimization to Make Sure Oracle Fusion Middleware R...Hardware and Software Co-optimization to Make Sure Oracle Fusion Middleware R...
Hardware and Software Co-optimization to Make Sure Oracle Fusion Middleware R...
 
Cassandra TK 2014 - Large Nodes
Cassandra TK 2014 - Large NodesCassandra TK 2014 - Large Nodes
Cassandra TK 2014 - Large Nodes
 
Toshiba Storage Protfolio 2014
Toshiba Storage Protfolio 2014Toshiba Storage Protfolio 2014
Toshiba Storage Protfolio 2014
 
Alibaba cloud benchmarking report ecs rds limton xavier
Alibaba cloud benchmarking report ecs  rds limton xavierAlibaba cloud benchmarking report ecs  rds limton xavier
Alibaba cloud benchmarking report ecs rds limton xavier
 
Ceph Day Taipei - Accelerate Ceph via SPDK
Ceph Day Taipei - Accelerate Ceph via SPDK Ceph Day Taipei - Accelerate Ceph via SPDK
Ceph Day Taipei - Accelerate Ceph via SPDK
 
5 Things You Need to Know About Enterprise Fl
 5 Things You Need to Know About Enterprise Fl 5 Things You Need to Know About Enterprise Fl
5 Things You Need to Know About Enterprise Fl
 
Accelerating SSD Performance with HLNAND
Accelerating SSD Performance with HLNANDAccelerating SSD Performance with HLNAND
Accelerating SSD Performance with HLNAND
 
Big Lab Problems Solved with Spectrum Scale: Innovations for the Coral Program
Big Lab Problems Solved with Spectrum Scale: Innovations for the Coral ProgramBig Lab Problems Solved with Spectrum Scale: Innovations for the Coral Program
Big Lab Problems Solved with Spectrum Scale: Innovations for the Coral Program
 
VMware VSAN Technical Deep Dive - March 2014
VMware VSAN Technical Deep Dive - March 2014VMware VSAN Technical Deep Dive - March 2014
VMware VSAN Technical Deep Dive - March 2014
 
Understanding and Measuring I/O Performance
Understanding and Measuring I/O PerformanceUnderstanding and Measuring I/O Performance
Understanding and Measuring I/O Performance
 
DevOps for ETL processing at scale with MongoDB, Solr, AWS and Chef
DevOps for ETL processing at scale with MongoDB, Solr, AWS and ChefDevOps for ETL processing at scale with MongoDB, Solr, AWS and Chef
DevOps for ETL processing at scale with MongoDB, Solr, AWS and Chef
 
stackArmor presentation for DevOpsDC ver 4
stackArmor presentation for DevOpsDC ver 4stackArmor presentation for DevOpsDC ver 4
stackArmor presentation for DevOpsDC ver 4
 
Stabilizing Ceph
Stabilizing CephStabilizing Ceph
Stabilizing Ceph
 

Mais de inside-BigData.com

Preparing to program Aurora at Exascale - Early experiences and future direct...
Preparing to program Aurora at Exascale - Early experiences and future direct...Preparing to program Aurora at Exascale - Early experiences and future direct...
Preparing to program Aurora at Exascale - Early experiences and future direct...inside-BigData.com
 
Transforming Private 5G Networks
Transforming Private 5G NetworksTransforming Private 5G Networks
Transforming Private 5G Networksinside-BigData.com
 
The Incorporation of Machine Learning into Scientific Simulations at Lawrence...
The Incorporation of Machine Learning into Scientific Simulations at Lawrence...The Incorporation of Machine Learning into Scientific Simulations at Lawrence...
The Incorporation of Machine Learning into Scientific Simulations at Lawrence...inside-BigData.com
 
How to Achieve High-Performance, Scalable and Distributed DNN Training on Mod...
How to Achieve High-Performance, Scalable and Distributed DNN Training on Mod...How to Achieve High-Performance, Scalable and Distributed DNN Training on Mod...
How to Achieve High-Performance, Scalable and Distributed DNN Training on Mod...inside-BigData.com
 
Evolving Cyberinfrastructure, Democratizing Data, and Scaling AI to Catalyze ...
Evolving Cyberinfrastructure, Democratizing Data, and Scaling AI to Catalyze ...Evolving Cyberinfrastructure, Democratizing Data, and Scaling AI to Catalyze ...
Evolving Cyberinfrastructure, Democratizing Data, and Scaling AI to Catalyze ...inside-BigData.com
 
HPC Impact: EDA Telemetry Neural Networks
HPC Impact: EDA Telemetry Neural NetworksHPC Impact: EDA Telemetry Neural Networks
HPC Impact: EDA Telemetry Neural Networksinside-BigData.com
 
Biohybrid Robotic Jellyfish for Future Applications in Ocean Monitoring
Biohybrid Robotic Jellyfish for Future Applications in Ocean MonitoringBiohybrid Robotic Jellyfish for Future Applications in Ocean Monitoring
Biohybrid Robotic Jellyfish for Future Applications in Ocean Monitoringinside-BigData.com
 
Machine Learning for Weather Forecasts
Machine Learning for Weather ForecastsMachine Learning for Weather Forecasts
Machine Learning for Weather Forecastsinside-BigData.com
 
HPC AI Advisory Council Update
HPC AI Advisory Council UpdateHPC AI Advisory Council Update
HPC AI Advisory Council Updateinside-BigData.com
 
Fugaku Supercomputer joins fight against COVID-19
Fugaku Supercomputer joins fight against COVID-19Fugaku Supercomputer joins fight against COVID-19
Fugaku Supercomputer joins fight against COVID-19inside-BigData.com
 
Energy Efficient Computing using Dynamic Tuning
Energy Efficient Computing using Dynamic TuningEnergy Efficient Computing using Dynamic Tuning
Energy Efficient Computing using Dynamic Tuninginside-BigData.com
 
HPC at Scale Enabled by DDN A3i and NVIDIA SuperPOD
HPC at Scale Enabled by DDN A3i and NVIDIA SuperPODHPC at Scale Enabled by DDN A3i and NVIDIA SuperPOD
HPC at Scale Enabled by DDN A3i and NVIDIA SuperPODinside-BigData.com
 
Versal Premium ACAP for Network and Cloud Acceleration
Versal Premium ACAP for Network and Cloud AccelerationVersal Premium ACAP for Network and Cloud Acceleration
Versal Premium ACAP for Network and Cloud Accelerationinside-BigData.com
 
Zettar: Moving Massive Amounts of Data across Any Distance Efficiently
Zettar: Moving Massive Amounts of Data across Any Distance EfficientlyZettar: Moving Massive Amounts of Data across Any Distance Efficiently
Zettar: Moving Massive Amounts of Data across Any Distance Efficientlyinside-BigData.com
 
Scaling TCO in a Post Moore's Era
Scaling TCO in a Post Moore's EraScaling TCO in a Post Moore's Era
Scaling TCO in a Post Moore's Erainside-BigData.com
 
CUDA-Python and RAPIDS for blazing fast scientific computing
CUDA-Python and RAPIDS for blazing fast scientific computingCUDA-Python and RAPIDS for blazing fast scientific computing
CUDA-Python and RAPIDS for blazing fast scientific computinginside-BigData.com
 
Introducing HPC with a Raspberry Pi Cluster
Introducing HPC with a Raspberry Pi ClusterIntroducing HPC with a Raspberry Pi Cluster
Introducing HPC with a Raspberry Pi Clusterinside-BigData.com
 

Mais de inside-BigData.com (20)

Major Market Shifts in IT
Major Market Shifts in ITMajor Market Shifts in IT
Major Market Shifts in IT
 
Preparing to program Aurora at Exascale - Early experiences and future direct...
Preparing to program Aurora at Exascale - Early experiences and future direct...Preparing to program Aurora at Exascale - Early experiences and future direct...
Preparing to program Aurora at Exascale - Early experiences and future direct...
 
Transforming Private 5G Networks
Transforming Private 5G NetworksTransforming Private 5G Networks
Transforming Private 5G Networks
 
The Incorporation of Machine Learning into Scientific Simulations at Lawrence...
The Incorporation of Machine Learning into Scientific Simulations at Lawrence...The Incorporation of Machine Learning into Scientific Simulations at Lawrence...
The Incorporation of Machine Learning into Scientific Simulations at Lawrence...
 
How to Achieve High-Performance, Scalable and Distributed DNN Training on Mod...
How to Achieve High-Performance, Scalable and Distributed DNN Training on Mod...How to Achieve High-Performance, Scalable and Distributed DNN Training on Mod...
How to Achieve High-Performance, Scalable and Distributed DNN Training on Mod...
 
Evolving Cyberinfrastructure, Democratizing Data, and Scaling AI to Catalyze ...
Evolving Cyberinfrastructure, Democratizing Data, and Scaling AI to Catalyze ...Evolving Cyberinfrastructure, Democratizing Data, and Scaling AI to Catalyze ...
Evolving Cyberinfrastructure, Democratizing Data, and Scaling AI to Catalyze ...
 
HPC Impact: EDA Telemetry Neural Networks
HPC Impact: EDA Telemetry Neural NetworksHPC Impact: EDA Telemetry Neural Networks
HPC Impact: EDA Telemetry Neural Networks
 
Biohybrid Robotic Jellyfish for Future Applications in Ocean Monitoring
Biohybrid Robotic Jellyfish for Future Applications in Ocean MonitoringBiohybrid Robotic Jellyfish for Future Applications in Ocean Monitoring
Biohybrid Robotic Jellyfish for Future Applications in Ocean Monitoring
 
Machine Learning for Weather Forecasts
Machine Learning for Weather ForecastsMachine Learning for Weather Forecasts
Machine Learning for Weather Forecasts
 
HPC AI Advisory Council Update
HPC AI Advisory Council UpdateHPC AI Advisory Council Update
HPC AI Advisory Council Update
 
Fugaku Supercomputer joins fight against COVID-19
Fugaku Supercomputer joins fight against COVID-19Fugaku Supercomputer joins fight against COVID-19
Fugaku Supercomputer joins fight against COVID-19
 
Energy Efficient Computing using Dynamic Tuning
Energy Efficient Computing using Dynamic TuningEnergy Efficient Computing using Dynamic Tuning
Energy Efficient Computing using Dynamic Tuning
 
HPC at Scale Enabled by DDN A3i and NVIDIA SuperPOD
HPC at Scale Enabled by DDN A3i and NVIDIA SuperPODHPC at Scale Enabled by DDN A3i and NVIDIA SuperPOD
HPC at Scale Enabled by DDN A3i and NVIDIA SuperPOD
 
State of ARM-based HPC
State of ARM-based HPCState of ARM-based HPC
State of ARM-based HPC
 
Versal Premium ACAP for Network and Cloud Acceleration
Versal Premium ACAP for Network and Cloud AccelerationVersal Premium ACAP for Network and Cloud Acceleration
Versal Premium ACAP for Network and Cloud Acceleration
 
Zettar: Moving Massive Amounts of Data across Any Distance Efficiently
Zettar: Moving Massive Amounts of Data across Any Distance EfficientlyZettar: Moving Massive Amounts of Data across Any Distance Efficiently
Zettar: Moving Massive Amounts of Data across Any Distance Efficiently
 
Scaling TCO in a Post Moore's Era
Scaling TCO in a Post Moore's EraScaling TCO in a Post Moore's Era
Scaling TCO in a Post Moore's Era
 
CUDA-Python and RAPIDS for blazing fast scientific computing
CUDA-Python and RAPIDS for blazing fast scientific computingCUDA-Python and RAPIDS for blazing fast scientific computing
CUDA-Python and RAPIDS for blazing fast scientific computing
 
Introducing HPC with a Raspberry Pi Cluster
Introducing HPC with a Raspberry Pi ClusterIntroducing HPC with a Raspberry Pi Cluster
Introducing HPC with a Raspberry Pi Cluster
 
Overview of HPC Interconnects
Overview of HPC InterconnectsOverview of HPC Interconnects
Overview of HPC Interconnects
 

Último

Understanding Discord NSFW Servers A Guide for Responsible Users.pdf
Understanding Discord NSFW Servers A Guide for Responsible Users.pdfUnderstanding Discord NSFW Servers A Guide for Responsible Users.pdf
Understanding Discord NSFW Servers A Guide for Responsible Users.pdfUK Journal
 
2024: Domino Containers - The Next Step. News from the Domino Container commu...
2024: Domino Containers - The Next Step. News from the Domino Container commu...2024: Domino Containers - The Next Step. News from the Domino Container commu...
2024: Domino Containers - The Next Step. News from the Domino Container commu...Martijn de Jong
 
Boost Fertility New Invention Ups Success Rates.pdf
Boost Fertility New Invention Ups Success Rates.pdfBoost Fertility New Invention Ups Success Rates.pdf
Boost Fertility New Invention Ups Success Rates.pdfsudhanshuwaghmare1
 
A Domino Admins Adventures (Engage 2024)
A Domino Admins Adventures (Engage 2024)A Domino Admins Adventures (Engage 2024)
A Domino Admins Adventures (Engage 2024)Gabriella Davis
 
08448380779 Call Girls In Diplomatic Enclave Women Seeking Men
08448380779 Call Girls In Diplomatic Enclave Women Seeking Men08448380779 Call Girls In Diplomatic Enclave Women Seeking Men
08448380779 Call Girls In Diplomatic Enclave Women Seeking MenDelhi Call girls
 
The Role of Taxonomy and Ontology in Semantic Layers - Heather Hedden.pdf
The Role of Taxonomy and Ontology in Semantic Layers - Heather Hedden.pdfThe Role of Taxonomy and Ontology in Semantic Layers - Heather Hedden.pdf
The Role of Taxonomy and Ontology in Semantic Layers - Heather Hedden.pdfEnterprise Knowledge
 
Finology Group – Insurtech Innovation Award 2024
Finology Group – Insurtech Innovation Award 2024Finology Group – Insurtech Innovation Award 2024
Finology Group – Insurtech Innovation Award 2024The Digital Insurer
 
Strategies for Landing an Oracle DBA Job as a Fresher
Strategies for Landing an Oracle DBA Job as a FresherStrategies for Landing an Oracle DBA Job as a Fresher
Strategies for Landing an Oracle DBA Job as a FresherRemote DBA Services
 
Boost PC performance: How more available memory can improve productivity
Boost PC performance: How more available memory can improve productivityBoost PC performance: How more available memory can improve productivity
Boost PC performance: How more available memory can improve productivityPrincipled Technologies
 
What Are The Drone Anti-jamming Systems Technology?
What Are The Drone Anti-jamming Systems Technology?What Are The Drone Anti-jamming Systems Technology?
What Are The Drone Anti-jamming Systems Technology?Antenna Manufacturer Coco
 
[2024]Digital Global Overview Report 2024 Meltwater.pdf
[2024]Digital Global Overview Report 2024 Meltwater.pdf[2024]Digital Global Overview Report 2024 Meltwater.pdf
[2024]Digital Global Overview Report 2024 Meltwater.pdfhans926745
 
EIS-Webinar-Prompt-Knowledge-Eng-2024-04-08.pptx
EIS-Webinar-Prompt-Knowledge-Eng-2024-04-08.pptxEIS-Webinar-Prompt-Knowledge-Eng-2024-04-08.pptx
EIS-Webinar-Prompt-Knowledge-Eng-2024-04-08.pptxEarley Information Science
 
08448380779 Call Girls In Civil Lines Women Seeking Men
08448380779 Call Girls In Civil Lines Women Seeking Men08448380779 Call Girls In Civil Lines Women Seeking Men
08448380779 Call Girls In Civil Lines Women Seeking MenDelhi Call girls
 
Workshop - Best of Both Worlds_ Combine KG and Vector search for enhanced R...
Workshop - Best of Both Worlds_ Combine  KG and Vector search for  enhanced R...Workshop - Best of Both Worlds_ Combine  KG and Vector search for  enhanced R...
Workshop - Best of Both Worlds_ Combine KG and Vector search for enhanced R...Neo4j
 
ProductAnonymous-April2024-WinProductDiscovery-MelissaKlemke
ProductAnonymous-April2024-WinProductDiscovery-MelissaKlemkeProductAnonymous-April2024-WinProductDiscovery-MelissaKlemke
ProductAnonymous-April2024-WinProductDiscovery-MelissaKlemkeProduct Anonymous
 
🐬 The future of MySQL is Postgres 🐘
🐬  The future of MySQL is Postgres   🐘🐬  The future of MySQL is Postgres   🐘
🐬 The future of MySQL is Postgres 🐘RTylerCroy
 
Data Cloud, More than a CDP by Matt Robison
Data Cloud, More than a CDP by Matt RobisonData Cloud, More than a CDP by Matt Robison
Data Cloud, More than a CDP by Matt RobisonAnna Loughnan Colquhoun
 
How to convert PDF to text with Nanonets
How to convert PDF to text with NanonetsHow to convert PDF to text with Nanonets
How to convert PDF to text with Nanonetsnaman860154
 
Partners Life - Insurer Innovation Award 2024
Partners Life - Insurer Innovation Award 2024Partners Life - Insurer Innovation Award 2024
Partners Life - Insurer Innovation Award 2024The Digital Insurer
 
IAC 2024 - IA Fast Track to Search Focused AI Solutions
IAC 2024 - IA Fast Track to Search Focused AI SolutionsIAC 2024 - IA Fast Track to Search Focused AI Solutions
IAC 2024 - IA Fast Track to Search Focused AI SolutionsEnterprise Knowledge
 

Último (20)

Understanding Discord NSFW Servers A Guide for Responsible Users.pdf
Understanding Discord NSFW Servers A Guide for Responsible Users.pdfUnderstanding Discord NSFW Servers A Guide for Responsible Users.pdf
Understanding Discord NSFW Servers A Guide for Responsible Users.pdf
 
2024: Domino Containers - The Next Step. News from the Domino Container commu...
2024: Domino Containers - The Next Step. News from the Domino Container commu...2024: Domino Containers - The Next Step. News from the Domino Container commu...
2024: Domino Containers - The Next Step. News from the Domino Container commu...
 
Boost Fertility New Invention Ups Success Rates.pdf
Boost Fertility New Invention Ups Success Rates.pdfBoost Fertility New Invention Ups Success Rates.pdf
Boost Fertility New Invention Ups Success Rates.pdf
 
A Domino Admins Adventures (Engage 2024)
A Domino Admins Adventures (Engage 2024)A Domino Admins Adventures (Engage 2024)
A Domino Admins Adventures (Engage 2024)
 
08448380779 Call Girls In Diplomatic Enclave Women Seeking Men
08448380779 Call Girls In Diplomatic Enclave Women Seeking Men08448380779 Call Girls In Diplomatic Enclave Women Seeking Men
08448380779 Call Girls In Diplomatic Enclave Women Seeking Men
 
The Role of Taxonomy and Ontology in Semantic Layers - Heather Hedden.pdf
The Role of Taxonomy and Ontology in Semantic Layers - Heather Hedden.pdfThe Role of Taxonomy and Ontology in Semantic Layers - Heather Hedden.pdf
The Role of Taxonomy and Ontology in Semantic Layers - Heather Hedden.pdf
 
Finology Group – Insurtech Innovation Award 2024
Finology Group – Insurtech Innovation Award 2024Finology Group – Insurtech Innovation Award 2024
Finology Group – Insurtech Innovation Award 2024
 
Strategies for Landing an Oracle DBA Job as a Fresher
Strategies for Landing an Oracle DBA Job as a FresherStrategies for Landing an Oracle DBA Job as a Fresher
Strategies for Landing an Oracle DBA Job as a Fresher
 
Boost PC performance: How more available memory can improve productivity
Boost PC performance: How more available memory can improve productivityBoost PC performance: How more available memory can improve productivity
Boost PC performance: How more available memory can improve productivity
 
What Are The Drone Anti-jamming Systems Technology?
What Are The Drone Anti-jamming Systems Technology?What Are The Drone Anti-jamming Systems Technology?
What Are The Drone Anti-jamming Systems Technology?
 
[2024]Digital Global Overview Report 2024 Meltwater.pdf
[2024]Digital Global Overview Report 2024 Meltwater.pdf[2024]Digital Global Overview Report 2024 Meltwater.pdf
[2024]Digital Global Overview Report 2024 Meltwater.pdf
 
EIS-Webinar-Prompt-Knowledge-Eng-2024-04-08.pptx
EIS-Webinar-Prompt-Knowledge-Eng-2024-04-08.pptxEIS-Webinar-Prompt-Knowledge-Eng-2024-04-08.pptx
EIS-Webinar-Prompt-Knowledge-Eng-2024-04-08.pptx
 
08448380779 Call Girls In Civil Lines Women Seeking Men
08448380779 Call Girls In Civil Lines Women Seeking Men08448380779 Call Girls In Civil Lines Women Seeking Men
08448380779 Call Girls In Civil Lines Women Seeking Men
 
Workshop - Best of Both Worlds_ Combine KG and Vector search for enhanced R...
Workshop - Best of Both Worlds_ Combine  KG and Vector search for  enhanced R...Workshop - Best of Both Worlds_ Combine  KG and Vector search for  enhanced R...
Workshop - Best of Both Worlds_ Combine KG and Vector search for enhanced R...
 
ProductAnonymous-April2024-WinProductDiscovery-MelissaKlemke
ProductAnonymous-April2024-WinProductDiscovery-MelissaKlemkeProductAnonymous-April2024-WinProductDiscovery-MelissaKlemke
ProductAnonymous-April2024-WinProductDiscovery-MelissaKlemke
 
🐬 The future of MySQL is Postgres 🐘
🐬  The future of MySQL is Postgres   🐘🐬  The future of MySQL is Postgres   🐘
🐬 The future of MySQL is Postgres 🐘
 
Data Cloud, More than a CDP by Matt Robison
Data Cloud, More than a CDP by Matt RobisonData Cloud, More than a CDP by Matt Robison
Data Cloud, More than a CDP by Matt Robison
 
How to convert PDF to text with Nanonets
How to convert PDF to text with NanonetsHow to convert PDF to text with Nanonets
How to convert PDF to text with Nanonets
 
Partners Life - Insurer Innovation Award 2024
Partners Life - Insurer Innovation Award 2024Partners Life - Insurer Innovation Award 2024
Partners Life - Insurer Innovation Award 2024
 
IAC 2024 - IA Fast Track to Search Focused AI Solutions
IAC 2024 - IA Fast Track to Search Focused AI SolutionsIAC 2024 - IA Fast Track to Search Focused AI Solutions
IAC 2024 - IA Fast Track to Search Focused AI Solutions
 

Lustre client performance comparison and tuning (1.8.x to 2.x)

  • 1. Lustre 1.8.9 - 2.x Client Performance Comparison and Tuning! John Fragalla! HPC Principal Architect! Xyratex, A Seagate Company! ! Lustre User Group Conference! April 8-10, 2014!
  • 2. • Benchmark Setup! • IOR Parameters and Settings! • Lustre Clients and Methodology! • Single Thread Performance! • Throughput Performance Results and Data! • Summary! Agenda! !
  • 3. • Storage Architecture! – A Cluster 6000 SSU with GridRaid OSTs! •  Rated Storage Performance ≥ 6 GB/s Read or Write with IOR! – InfiniBand FDR Interconnect! – Xyratex Lustre 2.1.0.x4-74! • Client Hardware! – 8 Clients, each configured with QDR IB, 48GB Memory and 12 Cores! – Scientific Linux 6.5 with Stock OFED! Benchmark Setup!
  • 4. • Used mpirun to execute IOR with --byslot distribution! • IOR Parameters that were constant:! –  -F : File Per Process! –  -B : Direct IO Operation! –  -t 64m: 64m Transfer Size per Task! –  -b: 1024g for Single Thread and 512g for multiple tasks! –  -D: stonewall option, write for 4 minutes, and read for 2 minutes! • Lustre Settings! – Stripe Count of 1! – Stripe Size of 1m! IOR Parameters and Settings!
  • 5. • Compared the following clients:! – 1.8.9, 2.1.6, 2.4.3, and 2.5.1! • Collected raw performance data using the following client settings with and without checksums enabled! – max_rpcs_in flight / max_dirty_mb! •  32 / 128! •  64 / 256! •  128 / 512! •  256 / 1024! Lustre Clients!
  • 6. Single Thread Write Performance! 0 200 400 600 800 1,000 1,200 32/128 64/256 128/512 256/1024 MB/s Max PRCs / Max Dirty MB Single Thread Client Write Performance - Checksums Disabled 1.8.9 CS=0 Write (MB/s) 2.1.6 CS=0 Write (MB/s) 2.4.3 CS=0 Write (MB/s) 2.5.1 CS=0 Write (MB/s)
  • 7. Single Thread Read Performance! - 200.00 400.00 600.00 800.00 1,000.00 1,200.00 1,400.00 32/128 64/256 128/512 256/1024 MB/s Max PRCs / Max Dirty MB Single Thread Client Read Performance Checksums Disabled 1.8.9 CS=0 Read (MB/s) 2.1.6 CS=0 Read (MB/s) 2.4.3 CS=0 Read (MB/s) 2.5.1 CS=0 Read (MB/s)
  • 8. Impact on Single Thread Performance when Checksums were Enabled!  ! Checksums Impact - Single Thread!  Version!  ! Reads! Writes! 1.8.9! Performance Impact Difference (MB/s)! 217.80 ! 336.84 ! Percentage Impact Reduced! 19%! 35%! 2.1.6! Performance Impact Difference (MB/s)! 37.70 ! 27.81 ! Percentage Impact Reduced! 3%! 6%! 2.4.3! Performance Impact Difference (MB/s)! 45.51 ! 9.14 ! Percentage Impact Reduced! 6%! 1%! 2.5.1! Performance Impact Difference (MB/s)! 44.91 ! 6.50 ! Percentage Impact Reduced! 6%! 1%!
  • 9. 1.8.9 Client Performance Results! 0 1,000 2,000 3,000 4,000 5,000 6,000 7,000 1 2 4 8 8 8 4 8 16 32 64 96 MB/s Nodes and Tasks 1.8.9 Writes - Checksums Disabled Write 32/128/0 Write 64/256/0 Write 128/512/0 Write 256/1024/0 - 1,000 2,000 3,000 4,000 5,000 6,000 7,000 8,000 1 2 4 8 8 8 4 8 16 32 64 96 MB/s Nodes and Tasks 1.8.9 Reads - Checksums Disabled Read 32/128/0 Read 64/256/0 Read 128/512/0 Read 256/1024/0 Key: max_rpcs_in_flight / max_dirty_mb / checksums
  • 10. 2.1.6 Client Performance Results! 0 500 1,000 1,500 2,000 2,500 3,000 3,500 4,000 4,500 1 2 4 8 8 8 4 8 16 32 64 96 MB/s Nodes and Tasks 2.1.6 Writes - Checksums Disabled Write 32/128/0 Write 64/256/0 Write 128/512/0 Write 256/1024/0 0 1,000 2,000 3,000 4,000 5,000 6,000 1 2 4 8 8 8 4 8 16 32 64 96 MB/s Nodes and Tasks 2.1.6 Reads - Checksums Disabled Read 32/128/0 Read 64/256/0 Read 128/512/0 Read 256/1024/0 Key: max_rpcs_in_flight / max_dirty_mb / checksums
  • 11. 2.4.3 Client Performance Results! 0 1,000 2,000 3,000 4,000 5,000 6,000 7,000 1 2 4 8 8 8 4 8 16 32 64 96 MB/s Nodes and Tasks 2.4.3 Writes - Checksums Disabled Write 32/128/0 Write 64/256/0 Write 128/512/0 Write 256/1024/0 0 1,000 2,000 3,000 4,000 5,000 6,000 7,000 8,000 1 2 4 8 8 8 4 8 16 32 64 96 MB/s Nodes and Tasks 2.4.3 Reads - Checksums Disabled Read 32/128/0 Read 64/256/0 Read 128/512/0 Read 256/1024/0 Key: max_rpcs_in_flight / max_dirty_mb / checksums
  • 12. 2.5.1 Client Performance Results! 0 1,000 2,000 3,000 4,000 5,000 6,000 7,000 1 2 4 8 8 8 4 8 16 32 64 96 MB/s Nodes and Tasks 2.5.1 Writes - Checksums Disabled Write 32/128/0 Write 64/256/0 Write 128/512/0 Write 256/1024/0 0 1,000 2,000 3,000 4,000 5,000 6,000 7,000 8,000 1 2 4 8 8 8 4 8 16 32 64 96 MB/s Nodes and Tasks 2.5.1 Reads - Checksums Disabled Read 32/128/0 Read 64/256/0 Read 128/512/0 Read 256/1024/0 Key: max_rpcs_in_flight / max_dirty_mb / checksums
  • 13. Average Negative Impact on Performance when Checksums Enabled! Checksums Impact (max_rpcs_in_flight/max_dirty_mb) Reads 32/128 Write 32/128 Read 64/256 Write 65/256 Read 128/512 Write 128/512 Read 256/1024 Write 256/1024 1.8.9 Average Impact Difference (MB/s) 203.40 398.09 3.12 434.41 71.03 523.17 31.19 502.31 Average Impact Percentage 2% 10% -1% 10% 0% 13% 0% 12% 2.1.6 Average Impact Difference (MB/s) 541.64 269.93 446.17 196.06 445.79 189.33 453.34 180.07 Average Impact Percentage 22% 12% 19% 9% 18% 8% 9% 8% 2.4.3 Average Impact Difference (MB/s) 333.18 94.53 277.32 77.16 380.47 194.21 326.76 315.71 Average Impact Percentage 7% 3% 5% 2% 7% 4% 5% 6% 2.5.1 Average Impact Difference (MB/s) 486.11 161.09 245.24 154.50 366.05 256.85 346.78 423.12 Average Impact Percentage 12% 5% 5% 4% 6% 6% 6% 9% Average results using 4-96 Threads across 1-8 Clients
  • 14. 1.8.9, 2.4.3, 2.5.1 Overall Write Comparison! 0 1,000 2,000 3,000 4,000 5,000 6,000 7,000 1 2 4 8 8 8 4 8 16 32 64 96 MB/s Nodes and Tasks 1.8.9, 2.4.3, 2.5.1 Writes Comparison - Checksums Disabled 1.8.9 Write 32/128/0 1.8.9 Write 64/256/0 1.8.9 Write 128/512/0 1.8.9 Write 256/1024/0 2.4.3 Write 32/128/0 2.4.3 Write 64/256/0 2.4.3 Write 128/512/0 2.4.3 Write 256/1024/0 2.5.1 Write 32/128/0 2.5.1 Write 64/256/0 2.5.1 Write 128/512/0 2.5.1 Write 256/1024/0
  • 15. 1.8.9, 2.4.3, 2.5.1 Overall Read Comparison! 0 1,000 2,000 3,000 4,000 5,000 6,000 7,000 8,000 1 2 4 8 8 8 4 8 16 32 64 96 MB/s Nodes and Tasks 1.8.9, 2.4.3, 2.5.1 Reads Comparison - Checksums Disabled 1.8.9 Read 32/128/0 1.8.9 Read 64/256/0 1.8.9 Read 128/512/0 1.8.9 Read 256/1024/0 2.4.3 Read 32/128/0 2.4.3 Read 64/256/0 2.4.3 Read 128/512/0 2.4.3 Read 256/1024/0 2.5.1 Read 32/128/0 2.5.1 Read 64/256/0 2.5.1 Read 256/1024/0 2.5.1 Read 256/1024/0
  • 16. Maximizing Performance for Each Client! 0 1,000 2,000 3,000 4,000 5,000 6,000 7,000 8,000 32 32 96 96 32 32 32 32 Read 32/128/0 Write 32/128/0 Read 128/512/0 Write 128/512/0 Read 256/1024/0Write 256/1024/0Read 256/1024/0Write 256/1024/0 1.8.9 2.1.6 2.4.3 2.5.1 MB/s Client Reads and Writes RPCs/Dirty_MB/Checksums Max Performance Comparison - Checksums Disabled
  • 17. • In general, 1.8.9 Client performed the same regardless of client settings! • 2.4.3 and 2.5.1 followed the same performance curve! – Clients settings need to be increased to achieve maximum storage throughput! – Both max_rpcs_in_flight and max_dirty_mb need to be increased to at lest 256! •  Anything less than 256 will result in less than optimal Storage performance! • The rule of thumb: max_dirty_mb = max_rpcs_in_flight * 4 
 is not holding true with Client versions 2.4.3 and 2.5.1! Interesting Results Analyzing Raw Data!
  • 18. • 1.8.9 single thread performance results are the highest, but 2.4.3 and 2.5.1 improved over previous 2.x client versions! • With the right client settings, 2.4.3 and 2.5.1 client versions can maximize storage throughput, along with 1.8.9 clients! • 2.1.6 Client underperformed, regardless of client tuning! • Checksums impact varied with the number of threads, but, on average, not a “big” performance impact! – Biggest impact on performance with Checksums enabled was on the Single Thread tests! • 2.4.3 and 2.5.1 performance results were similar across all threads and client tuning parameters! Summary!